Both the second and third point are corroborated by prior work [1]}, [2]} as well as our own observations. The third point means that persistent states updated with shortrun Langevin can eventually act as longrun Langevin samples if the optimizer learning rate is small, because the EBM samples in previous timesteps are essentially samples from the current EBM.
